Improved Generative Adversarial Network for Rotating Component Fault Diagnosis in Scenarios With Extremely Limited Data
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2021.3127636
Abstract: Traditional data-driven intelligent fault diagnosis methods for rotating component commonly assume that sufficient labeled data is available. However, the rotary machine works in a normal state most of the time in practical engineering, resulting in… read more here.
Keywords: diagnosis scenarios; rotating component; fault diagnosis; diagnosis ... See more keywords